For a sorter, an ATM, a VTM, a vending machine, an automatic ticket machine and other intelligent processing devices for currency or notes, a core module is a valuable document recognition module. The performance of recognizing a valuable document is a core index for evaluating a valuable document recognition device. The index is affected by the following two factors in the large-scale application.
1) A first effect is operating environment. Changes in temperature, humidity and other environmental changes affect a precision sensor signal, thus affecting recognition accuracy for valuable documents.
2) A second effect is difference between valuable documents. There are significant differences between valuable documents of various areas. For example, the bill quality in urban areas is generally good, while the bill quality in rural areas is poor. Thus a same set of recognition standards cannot be well adapted to both conditions.
In view of the above problems, the following solutions are applied in the industry currently.
1) A sufficient number of samples of valuable documents are provided, which normally is required to be one thousand or more samples per category. Five or more devices are selected to collect sample signals under conditions of variety of temperature and humidity changes. The purpose is to collect as many categories and sample signals as possible for training recognition software, thus making the recognition adaptable to variety of different environments.
2) Different recognition software is used based on sample differences in different regions. That is, different versions of recognition software are customized according to actual needs.
However, the existing method of valuable document recognition requires a lot of resources. Furthermore, when the use environment changes, a response scheme have to be re-developed, which cannot guarantee long-term stable effect, not only increases the service cost of a provider, but also affects the market benefits.